Landscape Correlates of Breeding Bird Richness Across the United States Mid-Atlantic Region

Using a new set of landscape indicator data generated by the U.S.EPA, and a comprehensive breeding bird database from the National Breeding Bird Survey, we evaluated associations between breeding bird richness and landscape characteristics across the entire mid-Atlantic region of the United States. We evaluated how these relationships varied among different groupings (guilds) of birds based on functional, structural, and compositional aspects of individual species demographics. Forest edge was by far the most important landscape attribute affecting the richness of the lumped specialist and generalist guilds; specialist species richness was negatively associated with forest edge and generalist richness was positively associated with forest edge. Landscape variables (indicators) explained a greater proportion of specialist species richness than the generalist guild (46% and 31%, respectively). The lower value in generalists may reflect finer-scale distributions of open habitat that go undetected by the Landsat satellite, open habitats created by roads (the areas from which breeding bird data are obtained), and the lumping of a wide variety of species into the generalist category. A further breakdown of species into 16 guilds showed considerable variation in the response of breeding birds to landscape conditions; forest obligate species had the strongest association with landscape indicators measured in this study (55% of the total variation explained) and forest generalists and open ground nesters the lowest (17% of the total variation explained). The variable response of guild species richness to landscape pattern suggests that one must consider species' demographics when assessing the consequences of landscape change on breeding birds.     

Land Use Changes in Regional Economic Theory

Land use and land cover changes are a major source of environmental degradation and therefore a serious issue in sustainable development studies and in the integrated assessment of environmental problems. In an attempt to understand part of the complexity of land use change we here aim to explore the ways in which economists deals with the land use issue. We argue that space is one of the forgotten items in economics. Economists often seem to ignore high-resolution spatial dynamics either because they are not considered as an important feature of the problem or out of habit. It seems as though there is a trade-off between spatial resolution and human behaviour in current applications. Certain types of models are capable of capturing the spatial complexity of urban and regional areas, for instance, by using cellular automata. Other types of land use models clearly have shortcomings where it concerns spatial detail. Dynamic modelling approaches do not guarantee a high spatial resolution.We propose to give more attention to agent based modelling as this type of modelling provides a specific connection between processes on micro level and macro-level spatial structures.     

Application of statistical modeling to optimize a coastal water quality monitoring program

The long-term water quality monitoring program implemented by the Massachusetts Water Resources Authority in 1992 is extensive and has provide substantial understanding of the seasonality of the waters in both Boston Harbor and Massachusetts Bay and the response to improvements in effluent quality and offshore transfer of the effluent in September 2000. The monitoring program was designed with limited knowledge of spatial and temporal variability and long-term trends within the system. This led to an extensive spatial and temporal sampling program. The data through 2003 showed high correlation within physical parameters measured (e.g., salinity, dissolved oxygen) and in biological measures such as chlorophyll fluorescence. To address the potential sampling redundancies in the measurement program, an assessment of the impact of reduced levels of monitoring on the ability to make water quality decisions was completed. The optimization was conducted by applying statistical models that took into account whether there was evidence of a seasonal pattern in the data. The optimization used model survey average readings to identify temporal fixed effects, model survey-average-corrected individual station readings to identify spatial fixed effects, corrected the individual station readings for temporal and spatial fixed effects and derived a correlation model for the corrected data, and applied the correlation model to characterize the correlation of annual average readings from reduced monitoring programs with true parameter levels. Reductions in the number of sampling stations were found less detrimental to the quality of the data for annual decision-making than reductions in the number of surveys per year, although there is less of a difference in this regard for dissolved oxygen than there is for chlorophyll. The analysis led to recommendations for a substantially lower monitoring effort with minimal loss of information. The recommendation supported an annual budget savings of approximately $183,000. Most of the savings was from fewer surveys as approximately $21,000 came from the reduction in the number of stations monitored from 21 to 7 and associated laboratory analytical costs.     

An evaluation of selenium concentrations in water, sediment, invertebrates, and fish from the Solomon River Basin

The Solomon River Basin is located in north-central Kansas in an area underlain by marine geologic shales. Selenium is an indigenous constituent of these shales and is readily leached into the surrounding groundwater. Portions of the Basin are irrigated primarily through the pumping of selenium-contaminated groundwater from wells onto fields in agricultural production. Water, sediment, macroinvertebrates, and fish were collected from various sites in the Basin in 1998 and analyzed for selenium. Selenium concentrations were analyzed spatially and temporally and compared to reported selenium toxic effect thresholds for specific ecosystem components: water, sediments, food-chain organisms, and wholebody fish. A selenium aquatic hazard assessment for the Basin was determined based on protocol established by Lemly. Throughout the Basin, water, macroinvertebrate, and whole fish samples exceeded levels suspected of causing reproductive impairment in fish. Population structures of several fish species implied that successful reproduction was occurring; however, the influence of immigration of fish from low-selenium habitats could not be discounted. Site-specific fish reproduction studies are needed to determine the true impact of selenium on fishery resources in the Basin. The U.S. Government’s right to retain a non-exclusive, royalty free license in and to any copyright is acknowledged.     

The Role of Abatement Costs in GHG Permit Allocations: A Global Stabilization Scenario Analysis

Our objective is to propose permit allocation schemes that lead to a fair distribution of the net abatement cost among regions in a global greenhouse gas (GHG) stabilization scenario. We use a detailed technology-based energy model, World-MARKAL, to determine efficient abatement decisions, and to calculate the regional gross abatement costs (before permit allocation and trading). The net abatement costs are then calculated and used for different permit allocation schemes.     

Design and evaluation of an inlet conditioner to dry particles for real-time particle sizers

Real-time particle sizers provide rapid information about atmospheric particles, particularly peak exposures, which may be important in the development of adverse health outcomes. However, these instruments are subject to erroneous readings in high-humidity environments when compared with measurements from filter-based, federal reference method (FRM) samplers. Laboratory tests were conducted to evaluate the ability of three inlet conditioners to dry aerosol prior to entering a real-time particle sizer for measuring coarse aerosols (Model 3321 Aerodynamic Particle Sizer, APS) under simulated highly humid conditions. Two 30 day field studies in Birmingham, AL, USA were conducted to compare the response of two APSs operated with and without an inlet conditioner to that measured with FRM samplers. In field studies, the correlation of PM(10-2.5) derived from the APS and that measured with the FRM was substantially stronger with an inlet conditioner applied (r2 ranged from 0.91 to 0.99) than with no conditioner (r2 = 0.61). Laboratory experiments confirmed the ability of the heater and desiccant conditioner to remove particle-borne moisture. In field tests, water was found associated with particles across the sizing range of the APS (0.5 microm to 20 microm) when relative humidity was high in Birmingham. Certain types of inlet conditioners may substantially improve the correlation between particulate mass concentration derived from real-time particle sizers and filter-based samplers in humid conditions.     

Optimal Expansion Strategy for a Sewer System under Uncertainty

Because of fast urban sprawl, land use competition, and the gap in available funds and needed funds, municipal decision makers and planners are looking for more cost-effective and sustainable ways to improve their sewer infrastructure systems. The dominant approaches have turned to planning the sanitary sewer systems within a regional context, while the decentralized and on-site/cluster wastewater systems have not overcome the application barriers. But regionalization policy confers uncertainties and risks upon cities while planning for future events. Following the philosophy of smart growth, this paper presents several optimal expansion schemes for a fast-growing city in the US/Mexico borderlands—the city of Pharr in Texas under uncertainty. The waste stream generated in Pharr is divided into three distinct sewer sheds within the city limit, including south region, central region, and north region. The options available include routing the wastewater to a neighboring municipality (i.e., McAllen) for treatment and reuse, expanding the existing wastewater treatment plant (WWTP) in the south sewer shed, and constructing a new WWTP in the north sewer shed. Traditional deterministic least-cost optimization applied in the first stage can provide a cost-effective and technology-based decision without respect to associated uncertainties system wide. As the model is primarily driven by the fees charged for wastewater transfer, sensitivity analysis was emphasized by the inclusion of varying flat-rate fees for adjustable transfer schemes before contracting process that may support the assessment of fiscal benefits to all parties involved. Yet uncertainties might arise from wastewater generation, wastewater reuse, and cost increase in constructing and operating the new wastewater treatment plant simultaneously. When dealing with multiple sources of uncertainty, the grey mixed integer programming (GIP) model, formulated in the second stage, can further allow all sources of uncertainties to propagate throughout the optimization context, simultaneously leading to determine a wealth of optimal decisions within a reasonable range. Both models ran for three 5-year periods beginning in 2005 and ending in 2020. The dynamic outputs of this analysis reflect the systematic concerns about integrative uncertainties within this decision analysis, which enable decision makers and stakeholders to make all-inclusive decisions for sanitary sewer system expansion in an economically growing region.     

Modelling Tracer Dispersion from Landfills

Several wind tunnel experiments of tracer dispersion from reduced-scale landfill models are presented in this paper. Different experimental set-ups, hot-wire anemometry, particle image velocimetry and tracer concentration measurements were used for the characterisation of flow and dispersion phenomena nearby the models. The main aim of these experiments is to build an extensive experimental data set useful for model validation purposes. To demonstrate the potentiality of the experimental data set, a validation exercise on several mathematical models was performed by means of a statistical technique. The experiments highlighted an increase in pollutant ground level concentrations immediately downwind from the landfill because of induced turbulence and mean flow deflection. This phenomenon turns out to be predominant for the dispersion process. Tests with a different set-up showed an important dependence of the dispersion phenomena from the landfill height and highlighted how complex orographic conditions downwind of the landfill do not affect significantly the dispersion behaviour. Validation exercises were useful for model calibration, improving code reliability, as well as evaluating performances. The Van Ulden model proved to give the most encouraging results.     

A Model for Landscape Planning Under Complex Spatial Conditions

We present a new mathematical programming framework that is adaptable to a variety of spatially explicit landscape problems in environmental investment, conservation, and land-use planning, transport planning, and agriculture. As part of capturing spatial interdependencies, the framework considers decision variables at two levels, finely spaced grid cells and landholdings. We applied the framework to an environmental investment problem using objective functions representing biodiversity and carbon sequestration. We also tested the model to optimize the path of a road through part of the landscape. Using the Nambucca case study in eastern Australia, we applied a hybrid greedy randomised adaptive search procedure (GRASP) to find solutions to the model.     

Extension of the EUROS Integrated Air Quality Model to Fine Particulate Matter by Coupling to CACM/MADRID 2

The European Operational Smog (EUROS) integrated air quality modelling system has been extended to model fine particulate matter (PM). From an extended literature study, the Caltech Atmospheric Chemistry Mechanism and the Model of Aerosol Dynamics, Reaction, Ionisation and Dissolution were selected and recently coupled to EUROS. Currently, modelling of mass and chemical composition of aerosols in two size fractions (PM_2.5 and PM_10–2.5) is possible. The chemical composition is expressed in terms of seven components: ammonium, nitrate, sulphate, elementary carbon, primary inorganic compounds, primary organic compounds and secondary organic compounds. Calculated PM₁₀ concentrations and chemical composition are presented for two summer months of the year 2003 (1 July to 31 August).